Influencing factors for Pisa syndrome in patients with Parkinson's disease
Bibliographic record
Abstract
Objective To observe the clinical characteristics of Parkinson's disease (PD) patients complicated with Pisa syndrome (PS), and to explore the influencing factors for PS occurrence in the PD patients. Methods A nested case-control study was conducted on 222 patients continuously diagnosed with PD but not with lateral spinal flexion admitted in our department from September 2020 to December 2020. After 2 years of follow-up, 26 PD patients complicated with PS were assigned into observation group, and 98 sex- and age-matched PD patients without PS complication were assigned into control group in a ratio of 1 ∶4. Their demographic and clinical data were collected, and the relevant scales and questionnaires were performed, including Hoehn and Yahr (H-Y) Staging Scale, Parkinson's Disease Questionnaire-8 (PDQ-8), Unified Parkinson's Disease Rating Scale (UPDRS), Visual Analogue Scale (VAS), Montreal Cognitive Assessment Scale (MoCA), Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD). Results There were significant differences between the observation group and the control group in the course of the disease, equivalent daily dose of levodopa, drug adjustment, repeated falls within half a year, H-Y stage, UPDRS-Ⅲ score, score of axial symptoms, rigidity score, VAS score, PDQ-8 score, HAMA score, HAMD score and MoCA score (P < 0.05). Multivariate logistic regression analysis showed that the occurrence of PS was closely correlated with score of axial symptoms (OR=1.402, 95%CI=1.050~1.872, P=0.022), rigidity score (OR=1.429, 95%CI: 1.053~1.937, P=0.022) and VAS score (OR=1.772, 95%CI: 1.089~2.883, P=0.021). ROC curve analysis indicated that the AUC value of score of axial symptoms, rigidity score and VAS score was 0.899, 0.835 and 0.827, with a Youden index of 0.681, 0.558 and 0.488, respectively. Conclusion The severities of axial symptoms, rigidity and low back pain in PD patients are closely associated with the occurrence of PS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".